%0 Journal Article
%T Hierarchical audio classification algorithm for news video content analysis<br>面向新闻视频内容分析的音频分层分类算法*
%A JI Zhong
%A SU Yu-ting
%A SONG Xing-guang
%A AN Xin
%A <br>冀中
%A 苏育挺
%A 宋星光
%A 安欣
%J 计算机应用研究
%D 2009
%I 
%X This paper proposed hierarchical audio classification algorithm, which first classified the news audio stream into silence, speech and music with rule-based classifier, and then employed hidden Markov models to categorize the speech and music to male-anchor speech, female-anchor speech, alternate speech, monologue speech, live report and music. The experiment results show that the classification works best in male-anchor speech,female-anchor speech and music, in which precision and reall can both reach more than 90%. The classification performs worst in alternate speech with precision of 57.5% and with recall of 79.3%. The performance of classification in other types is at the average level with precision and recall ranging from 70% to 90%. Compared with the other representative algorithm, this method works well with relatively high precision.
%K audio classification
%K content analysis
%K hidden Markov model(HMM)
%K news video
%K video retrieval<br>音频分类
%K 内容分析
%K 隐马尔可夫模型
%K 新闻视频
%K 视频检索
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=8E38C5801F10F08C0742FF0BAA239D27&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=94C357A881DFC066&sid=2B71A0B813002B9E&eid=A43DA3A1D8511541&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=6